In this project, amplitudes of low-frequency fluctuations in resting-state fMRI data of subjects with Parkinson’s disease (PD) are studied and compared with matched normal controls. Empirical Mode Decomposition (EMD) is used to decompose the natural occurring frequency bands of major networks important in PD. The novelty of our approach lies in the data-adaptive decomposition of fMRI data using EMD, and identification of resting-state networks based on amplitude characteristics of intrinsic modes.
This abstract and the presentation materials are available to members only; a login is required.